Linkage mapping has proved to be an extremely powerful approach for identification of functional genes in protozoan parasites (Toxoplasma, Plasmodium, Trypanosomes), allowing identification of genes underlying important biomedical traits such as host specificity, virulence and drug resistance. Using classical linkage mapping we have identified a strong quantitative trait locus (QTL) (LOD = 21) for Oxamniquine resistance on chr 6 providing proof-of-principal that linkage mapping is also feasible for Schistosoma mansoni. However, classical linkage mapping is extremely labor intensive, logistically challenging and expensive, because both phenotypes and genotypes must be measured in individual F2 generation parasites. New X-QTL (or linkage group selection) methods, developed by researchers working on rodent malaria and yeast, promise to further expand the power of linkage mapping, because many 1000s of progeny can be effectively analyzed. In X-QTL analysis large pools of drug selected (or unselected) F2 progeny are quantitatively genotyped to identify selected genome regions. As this method does not require phenotyping and can effectively examine 1000s of pooled progeny, we believe it is well suited to S. mansoni. Our central goal is (a) to develop and validate efficient X-QTL methods for linkage analysis of S. mansoni and (b) to use these methods to identify the genes underlying important biomedical traits in this pathogen. We focus on drug resistance traits as these traits have a genetic basis and are biomedically important. Reduced cure rate following treatment with praziquantel (PZQ), the mainstay of Schistosomiasis control, has been reported from multiple foci and has a genetic basis; furthermore resistance to the second line drug oxamniquine (OXA) also occurs in nature. Initially, we will focus on OXA. We will validate X-QTL methods by comparing the QTLs identified by X-QTL with those identified using classical linkage mapping. In addition, we will use X-QTL to fine map the genome region containing OXA resistance. In aim 2 we will apply X-QTL approaches to map genome regions that underlie resistance to PZQ, using next generation sequencing both to genotype parental parasites and to accurately measure genome wide allele frequencies in large pools of treated or untreated F2 progeny. This work will be conducted using reduced representation libraries generated using sequence capture methods. By focusing on just 5Mb of the 363Mb genome we will be able to sequence pools to high read depth, measuring allele frequencies and QTL location with great accuracy and at low cost. Successful identification of genes that underlie drug response will allow development of molecular tools for monitoring resistance spread, provide insights into the mode of drug action, allow development of modified compounds that can kill resistant parasites. Most importantly, this project will establish efficient X-QTL linkage mapping approaches in the S. mansoni toolkit and set the stage for identification of the genetic determinants of a wide range of biomedically important traits in the major helminth pathogen infecting humans.